Saturation avoidance in digital imaging

ABSTRACT

A method of image capture helps avoid saturation in digital imaging. In one implementation, the method includes capturing a first digital image of a target using an electronic array light sensor, and identifying one or more saturated pixels in the first digital image. The method further includes identifying a region of interest in the first digital image, the region of interest encompassing the one or more identified saturated pixels. The method also includes capturing a second digital image of the target using the electronic array light sensor. The second digital image encompasses only the region of interest, and the second digital image is captured with a shorter exposure time than the first digital image. The first and second digital images may be combined into a high dynamic range image. Systems for digital imaging may be based on complementary metal oxide semiconductor (CMOS) or charge coupled device (CCD) sensors.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application claims the benefit of priority to U.S.Provisional Patent Application No. 62/745,610, filed Oct. 15, 2018 andtitled “Saturation Avoidance in Digital Imaging”, the contents of whichare hereby incorporated by reference herein in their entirety for allpurposes.

BACKGROUND OF THE INVENTION

Electrophoresis is a technique used in molecular biology and otherdisciplines to detect the presence of proteins or other analytes in amixture. Typically, after some preparatory steps, the mixture is placedin “wells” of a gel such as an agarose or polyacrylamide gel. For aprotein assay, the gel is subjected to an electric field, which causesthe proteins to migrate through the gel. The speed of migration of aparticular protein in the mixture through the gel is dependent on themolecular weight of the protein. Proteins having lower molecular weightstend to migrate faster than proteins having higher molecular weights.After a time, the different proteins become separated, since they havetraveled different distances through the gel.

The proteins may be tagged with antibodies such that the proteins ofinterest emit light by chemiluminescence. In some applications, forexample in the well-known western blotting technique, the proteins aretransferred to a membrane such as a polyvinylidene fluoride (PVDF) ornitrocellulose membrane to form a blot. Historically, (after a fewincubation steps) the blot was placed in contact with photographic filmof about the same size as the blot. The chemiluminescent light exposedportions of the film, so that the pattern of protein separations waspermanently recorded on the film. Recently, electronic imaging isreplacing photographic film for this purpose.

Contact imagers have been proposed for reading blot images. In a contactimager, the membrane is placed in contact or effectively in contact witha large semiconductor light sensor such as a CMOS (complementary metaloxide semiconductor) or CCD (charge coupled device) sensor. Lightemanated by chemiluminescence reaches the sensor directly, in much thesame way as in film-based contact recording. In this method, no shutteror other means is present for blocking light from the sample fromreaching the sensor, so the sensor is continuously exposed tochemiluminescent light from the sample. In addition, parts of the blotmay emanate much more light than other parts, requiring that the imagesystem have an extremely high dynamic range.

BRIEF SUMMARY OF THE INVENTION

According to one aspect, a method of image capture comprises capturing afirst digital image of a target using an electronic array light sensor,and identifying one or more saturated pixels in the first digital image.The method further comprises identifying a region of interest in thefirst digital image. The region of interest encompasses at least some ofthe one or more identified saturated pixels. The method furthercomprises capturing a second digital image of the target using theelectronic array light sensor, the second digital image encompassingonly the region of interest. The second digital image is captured with ashorter exposure time than the first digital image. In some embodiments,the first digital image encompasses the entire electronic array lightsensor, and is read as quickly as possible from the electronic arraylight sensor. In some embodiments, the region of interest encompassesall of the saturated pixels in the first digital image. In someembodiments, the region of interest encompasses a discrete patch ofsaturated pixels. In some embodiments, the region of interestencompasses only one of at least two discrete patches of saturatedpixels. In some embodiments, the method further comprises assembling ahigh dynamic range digital image of the target using at least the firstand second digital images. In some embodiments, the method furthercomprises capturing a long-exposure digital image of the target usingthe electronic array light sensor, the long-exposure digital image beingcaptured with an exposure time longer than the exposure time of thefirst digital image; and assembling the high dynamic range digital imageusing at least the first digital image, the second digital image, andthe long-exposure digital image. In some embodiments, the region ofinterest is a first region of interest, and the method further comprisesidentifying one or more saturated pixels in the second digital image;identifying a second region of interest encompassing at least some ofthe saturated pixels in the second digital image, the second region ofinterest being smaller than the first region of interest; and capturinga third digital image of the target using the electronic array lightsensor, the third digital image encompassing only the second region ofinterest, and the third digital image being captured with a shorterexposure time than the second digital image. In some embodiments, themethod further comprises assembling a high dynamic range digital imageof the target using at least the first digital image, the second digitalimage, and the third digital image. In some embodiments, the methodfurther comprises capturing a long-exposure digital image of the targetusing the electronic array light sensor, the long-exposure digital imagebeing captured with a longer exposure time than the first digital image;and assembling a high dynamic range digital image of the target using atleast the first digital image and the long-exposure digital image,wherein the second region of interest in the high dynamic range digitalimage includes data derived from the third digital image. In someembodiments, the region of interest is a first region of interest, andthe method further comprises identifying one or more saturated pixels inthe second digital image; subdividing the first region of interest intoone or more progressively smaller regions of interest; and capturing oneor more additional digital images of the one or more progressivelysmaller regions of interest using progressively smaller exposure times,until a digital image is obtained having no saturated pixels. In someembodiments, the electronic array light sensor is a complementary metaloxide semiconductor (CMOS) sensor, and capturing the second digitalimage of the target comprises reading fewer than all of the pixels inthe electronic array light sensor. In some embodiments, the electronicarray light sensor is a complementary metal oxide semiconductor (CMOS)sensor, and capturing at least one of the first digital image and thesecond digital image comprises the use of a rolling shutter. In someembodiments, the electronic array light sensor is a charge coupleddevice (CCD) sensor, and capturing the second digital image of thetarget comprises shifting some charges from the CCD sensor anddiscarding them without conversion to numerical values. In someembodiments, the electronic array light sensor is a charge coupleddevice (CCD) sensor, and capturing the second digital image of thetarget comprises binning of charges in the CCD sensor. In someembodiments, the method further comprises limiting the size of theregion of interest in relation to the electronic array light sensor. Insome embodiments, the second digital image is captured at a lowerresolution than the first digital image.

According to another aspect, an imaging device comprises an electronicarray light sensor having a number of pixels, and a controllerprogrammed to control the operation of the electronic array light sensorand to receive signals from the electronic array light sensor indicatingthe intensity of light falling respectively on the pixels of theelectronic array light sensor. The controller is programmed to capture afirst digital image of a target using the electronic array light sensor,identify one or more saturated pixels in the first digital image, andidentify a region of interest in the first digital image, the region ofinterest encompassing the one or more identified saturated pixels. Thecontroller is further programmed to capture a second digital image ofthe target using the electronic array light sensor, the second digitalimage encompassing only the region of interest, and the second digitalimage being captured with a shorter exposure time than the first digitalimage. In some embodiments, the electronic array light sensor is acomplementary metal oxide semiconductor (CMOS) sensor or a chargedcoupled device (CCD) sensor. In some embodiments, the controller isfurther programmed to construct a high dynamic range digital image ofthe target using at least the first digital image and the second digitalimage. In some embodiments, the controller is further programmed toidentify one or more saturated pixels in the second digital image;identify a second region of interest encompassing at least some of thesaturated pixels in the second digital image, the second region ofinterest being smaller than the first region of interest; and capture athird digital image of the target using the electronic array lightsensor, the third digital image encompassing only the second region ofinterest, and the third digital image being captured with a shorterexposure time than the second digital image. In some embodiments, theelectronic array light sensor comprises multiple taps.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a typical blot after separation of proteins, inaccordance with embodiments of the invention.

FIG. 2 illustrates an imaging device in accordance with embodiments ofthe invention, in a closed position.

FIG. 3 shows the imaging device of FIG. 2 in an open position.

FIG. 4 illustrates a target in the form of a blot similar to the blot ofFIG. 1, placed on a contact area image sensor of a device such as theimaging device of FIG. 2.

FIG. 5 illustrates a simplified block diagram of a CMOS image sensor, inaccordance with embodiments of the invention.

FIG. 6 illustrates a digital image as may be captured from the target ofFIG. 4.

FIG. 7 shows the digital image of FIG. 6, with additional annotation.

FIG. 8 illustrates a flowchart of a method in accordance withembodiments of the invention.

FIG. 9 illustrates a digital image of a region of the digital image ofFIG. 7, as captured more quickly than the digital image of FIG. 6.

FIG. 10 depicts a high dynamic range digital image assembled from thedigital images of FIGS. 6 and 9.

FIG. 11 illustrates another digital image in accordance with embodimentsof the invention.

FIG. 12 illustrates another digital image in accordance with embodimentsof the invention.

FIG. 13 illustrates another digital image in accordance with embodimentsof the invention.

FIG. 14 illustrates a flow chart of a method in accordance withembodiments of the invention.

FIG. 15 illustrates another digital image in accordance with embodimentsof the invention.

FIG. 16 illustrates another digital image in accordance with embodimentsof the invention.

FIG. 17 illustrates another digital image in accordance with embodimentsof the invention.

FIG. 18 shows the results of imaging certain regions of the digitalimage of FIG. 17, with shorter exposure times.

FIG. 19 illustrates an initial step in the construction of a highdynamic range image, in accordance with embodiments of the invention.

FIG. 20 illustrates another step in the construction of a high dynamicrange image, in accordance with embodiments of the invention.

FIG. 21 illustrates another step in the construction of a high dynamicrange image, in accordance with embodiments of the invention.

FIG. 22 illustrates a rolling shutter, in accordance with embodiments ofthe invention.

FIG. 23 illustrates a simplified block diagram of a CCD image sensor, inaccordance with embodiments of the invention.

FIG. 24 illustrates an imaging system in accordance with embodiments ofthe invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 illustrates a typical blot 100 after separation of proteins, inaccordance with embodiments of the invention. One lane 101 of the blotis reserved for protein standards 102 a-102 f. Protein standards 102a-102 f have been separated in direction 103, with lower molecularweight protein standard 102 f being farther from edge 104 than highermolecular weight protein standard 102 a.

Samples of the mixture to be assayed have been separated in lanes105-110, resulting in protein bands 111, 112, and 113 in each of lanes105-110. (The lane divisions shown in dashed lines are for illustrationonly, and do not appear on a blot.) Protein band 111 emits lightstrongly, and corresponds approximately to the molecular weight ofprotein standard 102 b. Protein band 112 emits light somewhat lessstrongly, and corresponds approximately to the molecular weight ofprotein standard 102 e. Protein band 113 corresponds approximately tothe molecular weight of protein standard 102 c, and emits light veryweakly, indicating that very little of the protein in band 113 may bepresent. Because standards 102 b, 102 c, and 102 e are of known weight,their presence provides information about the molecular weights of theproteins at bands 111, 112, and 113, to assist in identifying theproteins in bands 111, 112, and 113.

As is indicated in FIG. 1, the proteins in bands 111, 112, and 113 areemitting light via chemiluminescence. Protein standards 102 a-102 f mayor may not be chemiluminescent.

FIG. 2 illustrates an imaging device 200 in accordance with embodimentsof the invention, in a closed position. FIG. 3 shows imaging device 200in an open position.

Referring to both FIG. 2 and FIG. 3, imaging device 200 includes a baseportion 201 and a lid 202. Lid 202 is shown in a closed position in FIG.2, and in an open position in FIG. 3.

A contact area image sensor 301 is disposed in base 201. Contact areaimage sensor 301 is an example of an electronic array light sensor, andmay be, for example, of the kind described in U.S. Patent ApplicationPublication No. 2015/0172526 of Swihart et al., published Jun. 18, 2015and titled “Non-Destructive Read Operations with Dynamically GrowingImages”, now U.S. Pat. No. 9,736,388; U.S. Patent ApplicationPublication No. 2016/0006910 of Uri et al., published Jan. 7, 2016 andtitled “Contact Imager”, now U.S. Pat. No. 9,794,454; U.S. PatentApplication Publication No. 2016/0028976 of Ran et al., published Jan.28, 2016 and titled “Digital Imaging with Masked Pixels”, now U.S. Pat.No. 9,774,804; and U.S. Patent Application Publication No. 2017/0016829of Swihart et al., published Jan. 19, 2017 and titled “Contact ImagingDevices for Fluorescence Applications”, now U.S. Pat. No. 9,933,565, theentire disclosures of which are hereby incorporated by reference hereinfor all purposes.

Contact area image sensor 301 may be, for example, a charge coupleddevice (CCD) sensor, a complementary metal oxide semiconductor (CMOS)sensor, an organic photodiode sensor, or another suitable kind ofsensor. In general, such sensors exploit the property of somesemiconductor materials that when the material is struck by light, freeelectrons are generated in proportion to the intensity of the light. Thesensor is divided into specific light-sensitive areas called “pixels”.To capture an image, the pixels are reset and then exposed to light foran exposure time. At the end of the exposure time, the amount of chargeaccumulated in each pixel is measured and converted to a numericalvalue. An array of these numerical values may be called a “digitalimage”, with each value in the array representing the brightness of thelight falling on the corresponding pixel. In the digital image, thevalues may also be referred to as pixels.

In a CCD sensor, the accumulated charges are shifted off of the sensorto a charge amplifier, the output of which is digitized for each pixel.In a CMOS sensor, the accumulated charge can be read from each pixeldirectly, without shifting. In some sensors, different pixels aresensitive to different light wavelength bands, enabling color imaging.

In this context, a “contact” sensor is one that receives light directlyfrom locations on the target in contact with a face of the sensor, with1:1 magnification and without any intervening magnification-changingoptics. (There may be other kinds of optical components between thecontact surface and the light-sensitive semiconductor layer, for examplea fiber faceplate as described in U.S. Patent Application PublicationNo. 2017/0016829, previously incorporated by reference.) This kind ofsensing is analogous to the making of a “contact print” in filmphotography, in which a photographic negative is placed in directcontact with photo paper and exposed to light. An image is formed on thepaper that is the same size as the negative.

Referring again to FIG. 3, contact area image sensor 301 is preferablyslightly larger in area than a typical blot, for example about 7×10centimeters. In other embodiments, contact area image sensor 301 may beabout 5×7 inches, 8×10 inches, or 9×12 inches, or another suitable size.Contact area image sensor 301 preferably includes many thousands or evenmillions of pixels, which are small enough that a digital image capturedby contact area image sensor 301 provides a high resolutionrepresentation of a target placed on the sensor. For example, each pixelmay be about 130 microns square, or another suitable size. A sensor 7×10centimeters with 130-micron pixels would have about 414,000 totalpixels.

In FIG. 4, lid 202 has been opened, and a target 401 in the form of ablot similar to blot 100 is placed on contact area image sensor 301.Target 401 includes a lane 402 of protein standards that do not emitlight, as well as a number of locations 403 that do emit light bychemiluminescence, indicating the presence of particular proteins thathave been separated in the experiment. While only the top surface oftarget 401 is visible in FIG. 4, the chemiluminescent light is emittedfrom both sides, and some of the light is directed downward towardcontact area image sensor 301.

Once target 401 is in place, lid 202 is closed. Lid 202 shields contactarea image sensor 301 from ambient light when lid 202 is in the closedposition. With lid 202 in the closed position, digital images can becaptured if target 401 using contact area image sensor 301. To capture adigital image, image sensor 301 is flushed of accumulated charge, andthen read after a predetermined time called the exposure time. Inaddition, the act of reading contact area image sensor 301 takes afinite amount of time, as charges must be shifted off of the sensor (ina CCD sensor) or the pixels must be read sequentially (in a CMOSsensor).

In general, portions of target 401 where the chemiluminescence isstrongest will appear brighter in the digital image, and portions oftarget 401 where chemiluminescence is weaker or non-existent will appeardarker. The relative strength of the chemiluminescence may permit anapproximate quantification of the amounts of different proteins presentin the sample.

FIG. 5 illustrates a simplified block diagram of a CMOS image sensor 501having 64 pixels 502. In practice, CMOS sensors may have up to hundredsof thousands or millions of pixels. Each pixel 502 includes alight-sensitive area, and a number of transistors (not shown). Thetransistors enable selection of individual pixels by row selector 503and column selector 504, and conversion of the charge in the respectivepixel to a voltage. The voltage of the selected pixel is presented toanalog-to-digital converter (ADC) 505 for conversion to a digital value,which is output from the sensor at 506. Under control of timing logic507, pixels 502 can be reset (cleared of charge), exposed for apredetermined time, and read out through ADC 505. The resultingnumerical values can be collected by an external computer and assembledinto a digital image. A CMOS sensor has the advantage that pixels may beread out individually and selectively from any portion of the sensor; itis not necessary to read all of the pixels. In addition, ADC 505 may beformed in the same integrated circuit as pixels 502 in a CMOS sensor.

FIG. 6 illustrates a digital image 601 as may be captured from target401. The generation of digital image 601 from the output of contact areaimage sensor 301 may be accomplished in any suitable way. For example,imaging device 200 may contain a controller that performs all of thenecessary conversions and calculations, and stores digital image 601 ina standard image file format such as JPEG (Joint Photographic ExpertsGroup), TIFF (Tagged Image File Format), GIF (Graphics InterchangeFormat), PNG (Portable Network Graphics), or any other suitablestandardized or proprietary format. In other embodiments, signals may bepassed from imaging device 200 to a suitable computer system, whichconverts the signals and generates the digital image file. Any workablearchitecture and division of tasks may be used.

An electronic array light sensor such as contact area image sensor 301has inherent limitations. For example, each pixel of an electronic arraylight sensor has a finite capacity to accumulate charge. So long as theamount of charge stays below the pixel's charge capacity, the amount ofcharge is linearly proportional to the intensity of light that fell onthe pixel during the exposure time. However, when sufficient charge hasaccumulated to fill the pixel to capacity, any additional generatedelectrons are spilled into the substrate of the sensor, and no furthercharge is accumulated in the pixel. This condition is known assaturation. When a pixel has saturated, it is impossible to know theamount of light that fell on the pixel, except to note that the lightwas sufficient to saturate the pixel. And when two pixels are saturated,it is impossible to know if one of them may have received more lightthan the other, because the digital values read for the two pixels willbe the same. Stated another way, once saturation occurs, the pixel'sresponse is no longer linear.

Another inherent limitation of electronic array light sensors is noise.For example, even when a pixel is not exposed to light, it willaccumulate a small amount of charge, and may return a non-zero digitalvalue when read. This is known as dark noise. The amount of dark noisevaries from pixel to pixel, and is affected by the temperature of thepixel, among other factors. Dark noise may have a relatively fixedcomponent for each pixel (called fixed pattern dark noise), and a randomcomponent. Dark noise can make it difficult to read very low lightintensities, because the signal generated from exposure to the light maybe swamped by the dark noise. Many techniques have been developed forreducing or compensating for dark noise, including cooling the sensor,characterizing the dark noise to the extent possible and subtracting thecharacterized noise from subsequent images, and other techniques.

Another kind of noise inherent in electronic array light sensors iscalled shot noise. Shot noise results from random variation in thenumber of photons collected by a sensor pixel. Shot noise has aroot-mean-square value proportional to the square root of the imageintensity, and thus shot noise is much more significant in proportion tothe desired signal in low light conditions than in bright lightconditions. (The ratio of a number to its square root is larger forlarge numbers than for small numbers.) Thus, shot noise can alsocontribute to the difficulty of reading low light intensities. Due toits random nature, shot noise cannot be calibrated away. Techniques fordealing with shot noise may include taking images with long exposuretimes, or averaging multiple exposures.

Other noise sources exist in digital imaging as well, for example readnoise. In general, the more light that is available for imaging, theless noise will affect the final image. While fixed pattern noise can belargely compensated by proper calibration, random noise sources cannot.

These limitations—especially pixel charge capacity and darknoise—determine the dynamic range of a particular sensor. The dynamicrange indicates the range of image brightness that can be captured in asingle exposure, without saturation in the bright areas and with enoughsignal in the dark areas to distinguish the signal from noise.

Unfortunately, electrophoresis blots often produce very weak lightsignals in some areas and very bright signals in other areas, so thatthe brightness range of the blot far exceeds the dynamic range of atypical electronic array light sensor, even when steps are taken tocalibrate for noise as much as possible.

One technique that is sometimes used to deal with large ranges ofbrightness is called high dynamic range (HDR) imaging. In HDR imaging,two or more exposures are taken of the same scene (such as a blot), withdifferent exposure times. For example, one exposure may be very short,so that even the brightest areas of the blot do not saturate theircorresponding sensor pixels. A second exposure may be taken with a muchlonger exposure time. Chemiluminescent signals from the darkest part ofthe blot may not be detectable in the first short exposure, because thesignals are small in relation to the various noise sources. The signalsfrom the darker areas may be visible and distinguishable from noise inthe second, long exposure, but the brightest locations may be saturated.The two exposures are combined mathematically to create an HDR image.For example, the numerical values representing the brightest regions inthe first, short exposure image may be multiplied by the ratio of theexposure times, to estimate the numerical values that might have beenread for the bright pixels with the longer exposure time, had the pixelsnot saturated. In this way, the relative brightnesses of the bright anddim signals can be determined, even though it is not possible toaccurately capture both in a single exposure. In some applications, morethan two exposures may be taken, with graduated exposure times. In somecases, at least some of the multiple exposures may be captured usingnon-destructive reads performed during a single longer exposure. Suchtechniques are described in U.S. Patent Application Publication No.2015/0172526, previously incorporated by reference.

However, even HDR imaging as described above may not completelyeliminate saturation in some circumstances. For example, using a contactarea image sensor such as contact area image sensor 301, the minimumexposure time is determined by the finite amount of time it takes toread the image out of the sensor. Even if the sensor is reset andreading is initiated immediately, some pixels may saturate by the timethey are read. This problem may be exacerbated by higher resolutionsensors, which may take longer to read out than sensors having fewerpixels.

Embodiments of the invention use selective reading of portions of asensor to achieve shorter effective exposure times than are possiblewhen reading the entire sensor, to avoid saturation.

Digital image 601 is reproduced in FIG. 7 with additional annotation. Itis presumed that the signal pixels in region 701, corresponding toprotein band 111, have saturated, the signals pixels in region 703,corresponding to protein band 112 are relatively bright but notsaturated, and the signal pixels in region 702, corresponding to proteinband 113 are so dim as to be largely indistinguishable from noisepresent in this single-exposure image. Individual numerical values forcertain pixels are shown at 704. For example, if ADC 505 is an 8-bitconverter and the system is designed so that saturation of a pixelcorresponds to a full-scale reading of ADC 505, all of the numericalvalues in region 701 may be 255. The numerical values in region 703 maybe somewhat less than 255, for example an average of about 200, and thenumerical values in region 702 may be very small, for example onlyslightly larger on average than the values in the surrounding dark areasof the image that contain only readings of noise or background signalfrom the membrane. This example, having an 8-bit ADC and a range ofnumerical values of 0-255 is but one example. In other embodiments,different numbers of bits may be used, for example, 10 bits, 12 bits, 16bits, or another suitable number. In some embodiments, some digitalimages may be stored using floating point numbers.

Because the values in region 701 are saturated and the values in region702 are not readily distinguishable from noise, it is not possible toaccurately quantify the relative brightnesses of the chemiluminescencein the corresponding regions of target 401.

Conventional HDR imaging may not solve the problem, because thechemiluminescence corresponding to region 701 may be so bright that evenreading out the sensor as fast as possible may still result in saturatedpixels.

In accordance with embodiments of the invention, a digital image iscaptured using an entire electronic array light sensor, preferably asfast as possible so that the image has the shortest exposure timepossible, and the digital image is investigated to see if it containsany saturated pixels. If not, the image may satisfactorily serve as ashort-exposure-time image in a sequence of images used in HDR imaging.However, if the image contains saturated pixels, regions containing thesaturated pixels area identified and additional steps are performed toimage the identified regions without saturation.

FIG. 8 illustrates a flowchart of a method 800 in accordance withembodiments of the invention. In step 801, a first digital image iscaptured. For example, the first digital image may encompass the entireelectronic array light sensor, and may be taken as quickly as possible.That is, the sensor is cleared of charge and reading out is initiatedimmediately.

In step 802, the first digital image is investigated to see if itincludes any saturated pixels. For example (for an 8-bit system), thedigital values in the digital image may be checked one-by-one, to see ifany are 255. If no saturated pixels are identified (or in someembodiments only a negligible number of saturated pixels areidentified), conventional or other HDR imaging may be used. The firstdigital image may serve as the shortest-exposure-time image in theseries of digital images used in the HDR imaging process. In extremecases, images may be taken with exposure times ranging from less than 1millisecond to several minutes or more.

While embodiments of the invention are described as capturing digitalimages in increasing order of exposure time, this is not a requirement.In other embodiments, images may be captured in any order.

However, if saturated pixels are identified (or in some embodiments asignificant number of saturated pixels are found), a region of interestis identified that encompasses at least some of the saturated pixels.For example, in FIG. 7, region 701 encompasses all of the saturatedpixels in digital image 601. Region 701 is smaller than the entiredigital image. In this example, region 701 encompasses only about threepercent of the total area of digital image 601.

In step 804, a second digital image is captured, encompassing only theregion of interest. For example, the sensor is cleared of charge, andthe pixels in the region of interest are read out and converted tonumerical values. Because region 701 is much smaller than image 601, thesecond digital image can be read out much more quickly, and has a muchshorter exposure time. The pixels in region 701 therefore may not besaturated in the second digital image.

FIG. 9 illustrates a digital image 901 of region 701, as captured morequickly than digital image 601. Individual numerical values for certainpixels in digital image 901 are shown at 902. For example the pixelsthat were saturated in digital image 601 now have readings of about 120.The shorter exposure time for digital image 901 has eliminated thesaturation of these pixels.

Referring again to FIG. 8, at step 806, the second digital image 901 isexamined to see if it contains saturated pixels (which it does not inthe example so far). If not, then all of the area of the sample has beencharacterized in the linear range of the system, and the captured imagescan be assembled into an HDR image at step 807. In some embodiments,digital images 601 and 901 may be sufficient to assemble an HDR image.

For example, presuming that the exposure time of digital image 601 is 50milliseconds (a reasonable value for the time required to read out asensor) and the exposure time of digital image 901 is 5 milliseconds),protein bands 111 corresponding to region 701 result in about 24numerical counts per millisecond of exposure (120 counts/5milliseconds), while the somewhat dimmer protein bands 112 correspondingto region 703 result in about 4 numerical counts per millisecond ofexposure (200 counts/50 milliseconds). Thus, protein bands 111 are about6 times as bright as protein bands 112.

Put another way, the pixels sensing bright protein bands 111 would haveresulted in numerical values of about 1200 in digital image 601 (24counts/millisecond×50 milliseconds), if the system had not saturated.This relationship would have been impossible to determine using digitalimage 601 alone.

FIG. 10 depicts an HDR digital image 1001 assembled from first andsecond digital images 601 and 901, and normalized to an exposure time of50 milliseconds. The values for regions 702 and 703 are taken fromdigital image 601, and the values in region 701 are computed bymultiplying the values from digital image 901 by the ratio of theexposure times of the two images. Because an HDR image is a mathematicalconstruct rather than a single measurement, each of the numerical valuesmay use as many bits are needed, and “saturation” does not occur in theHDR image. In some embodiments, the HDR image may be stored usingfloating point values, to accommodate the large range of values.

In some embodiments, for example if the protein in protein bands 113 isnot of interest, then HDR image 1001 may be the final result. However,in some embodiments, further HDR imaging may be performed (step 808 ofFIG. 8) to determine other information about blot 100.

For example, a third digital image of blot 100 may be taken with a longexposure time, in an attempt to discern the relative brightness ofprotein bands 113 as compared with the other protein bands.

For example, FIG. 11 illustrates another digital image 1101, which inthis example is assumed to have an exposure time of 10 seconds, or 200times the exposure time of digital image 601 (and 2000 times theexposure time of digital image 901). In this image, the pixelscorresponding to protein bands 111 (corresponding to region 701) andprotein bands 112 (corresponding to region 703) have all saturated. Inaddition, the pixels corresponding to protein bands 113 (correspondingto region 702) have accumulated significant charge, and the overallbackground of the image has lightened slightly due to the accumulationof charge from various noise sources. However, because protein bands 113have actual chemiluminescence signal, the pixels corresponding to themhave lightened proportionally more than the background and are visibledue to the effect of random noise being less significant for largersignals. In this hypothetical example, the numerical valuescorresponding to protein bands 113 are on average about 59 counts abovethe background noise. Because the exposure time of digital image was 10seconds, or 10,000 milliseconds, protein bands 113 corresponding toregion 702 result in about 0.0059 numerical counts per millisecond ofexposure (59 counts/10,000 milliseconds).

HDR imaging has thus enabled the determination that thechemiluminescence of protein bands 111 is about 4,067 times as bright asthe chemiluminescence from protein bands 113 (24counts/millisecond/0.0059 counts/millisecond). This range of valueswould have been impossible to characterize using only digital imageswhose exposure times resulted in saturation of some pixels. By readingonly a region of interest from the sensor for certain bright pixels, theeffective dynamic range of the system (including HDR imaging) has beenfurther extended.

In some cases, even the technique described above may not be sufficientto eliminate saturation of all pixels. For example, for very brightchemiluminescence signals, even digital image 901 may be too large toread out before some of the pixels saturate. That is, referring to FIG.8, the test in step 806 may determine that some pixels are stillsaturated.

In that case, the region of interest corresponding to digital image 901may be further subdivided at step 809 shown in FIG. 8. For example, FIG.12 illustrates a digital image 1201 similar to digital image 601,preferably taken with an exposure time as short as possible for readingthe entire sensor, for example an exposure time of 50 milliseconds. Thepixels in region 1202 have saturated, as shown at 1203. As before, asecond digital image 1204 has been captured, encompassing only the partof the target corresponding to region 1202. Digital image 1204 may becaptured much faster than digital image 1201, for example with anexposure time of 5 milliseconds, because it uses only a portion of thesensor. However, as shown in FIG. 12, the pixels in digital image 1204are still saturated. That is, the chemiluminescence in the correspondingportions of the target is so bright that even the short exposure time ofdigital image 1204 cannon prevent saturation.

In this case, region 1202 may be further subdivided. For example, ratherthan using a region of interest encompassing all of the saturated pixelsin digital image 1201, discrete contiguous patches of saturated pixelsmay be isolated, for example in region 1205. The sensor is then reset,and a third digital image 1206 is taken with an even shorter exposuretime, for example 1 millisecond. In the example of FIG. 12, this thirddigital image has successfully read the pixels in region 1205 withoutsaturation, resulting in an average numerical value of about 130. Thebrightness of the chemiluminescence corresponding to region 1205 may becharacterized as about 130 counts per millisecond.

Referring again to FIG. 8, the test at step 810 will indicate thatsaturation has been avoided, and the first digital image 1201, seconddigital image 1204, and third digital image 1206 may be assembled intoan HDR image in step 811, as described above. Digital images may besimilarly captured of the other patches of saturated pixels in region1205 and assembled into the HDR image. Further HDR imaging may beperformed as desired, as shown at step 812.

The subdivision of regions of interest may be done in any suitablemanner. In the above example, each discrete patch of saturated pixelsdefined a separate region of interest, but this is not a requirement.Region 1202 could have been divided into two subregions including threepatches each of saturated pixels, and readable in about half the time asregion 1202. Or Region 1202 could have been divided into threesubregions including two patches each of saturated pixels, and readablein about one third the time as region 1202. Subregions may be selectedwithout regard to the boundaries of any patches of saturated pixels.Subregions need not be all of the same size, and may be any arbitraryportion of the region being subdivided.

And while two subdivisions of digital image 1201 were illustrated above,this is also not a limitation. As is shown in FIG. 8, if the test atstep 810 finds saturated pixels, the subdivision may be repeated as manytimes and to as fine a granularity as needed to avoid saturation, downto and including subregions containing only one pixel if necessary.

In some embodiments, limits may be placed on the size of subregions. Forexample, FIG. 13 illustrates a hypothetical blot image 1301, in whichwidely dispersed parts of the image contain saturated pixels. In thiscase, a region of interest 1302 encompassing all of the saturated pixelsin the image would be nearly as large as digital image 1301 itself, andtherefore would require nearly as much time to read. For this reason,the size of the regions of interest may be limited to a relatively smallfraction of the region being divided, for example, no more than 30%,40%, 50%, or another fraction of the region being divided. For example,if the saturated pixels in the first image encompass more than thelimiting percentage of the first image, then the first image may bearbitrarily divided into regions of image below the size limit, forexample into four or more equal-sized regions of interest, or in anotherway.

In the example of FIG. 12, regions of interest small enough to avoidsaturation were identified iteratively. First, region of interest 1202was defined encompassing all of the saturated pixels in the image, andwhen it was found that region of interest 1202 was not small enough toavoid saturation, it was further subdivided. In other embodiments, smallregions of interests may be identified directly, without such aniterative procedure.

For example, FIG. 14 illustrates a flow chart of a method 1400 inaccordance with such an embodiment. Steps 1401, 1402, and 1403 of method1400 are similar to steps 801, 802, and 803 of method 800 describedabove. A first image is captured at step 1401 using the entire sensorand preferably read as quickly as possible. If no saturated pixels arefound at step 1402, then other imaging may be performed at step 1403.

However, if the first digital image includes saturated pixels, then theimage area is divided into smaller regions of interest at step 1404,according to any suitable method. For example, the image area could bedivided into a fixed number of equal sized regions of interest. Or eachidentifiable patch of saturated pixels could be designated a region ofinterest. Any technique may be use, but preferably the technique dividesthe image area into small enough regions of interest that the regionscan be imaged much more quickly than the entire sensor.

For each of the identified regions of interest, an image of the regionof interest is captured at step 1406. The resulting image is checked atstep 1408 to see if it includes saturated pixels. If so, and if it isnot possible or desired to further subdivide the region of interest,then that particular region may not be usable for quantitative analysis,as shown at step 1407. In some embodiments, it may be possible to applyinterpolation techniques or other estimation techniques to estimate thetrue brightness of the saturated pixels.

Presuming the image of the current region of interest does not includesaturated pixels, the image is stored at step 1409, along with anindication of its exposure time, and control passes back to step 1406.

Once all of the regions of interest are processed, it may be desirableto re-image some of the regions. For example, any region in which thepixels are not close to saturation could be re-imaged with a longerexposure time, to capture a digital image with a better signal-to-noiseratio. Adjacent regions having similar brightnesses may be combined forre-imaging.

In any event, the stored digital images from the regions of interest canbe assembled into an HDR image at step 1411. Other imaging may beperformed as well, as shown by step 1412.

Compiling an HDR image may be performed in any workable way, but in someembodiments may be performed incrementally, as follows. FIG. 15illustrates a digital image 1501 serving as an example. Using techniquesdescribed above, two regions of interest 1502 and 1503 have beenidentified as containing saturated pixels. For the sake of example, theexposure time for digital image 1501 was 50 milliseconds. Each ofregions 1502 and 1503 is small in comparison to the entire digital image1501, and can be read much more quickly. For example, FIG. 16illustrates a digital image 1601, which was collected from region ofinterest 1502 with an exposure time of 10 milliseconds. As is apparent,at a 10 millisecond exposure time, the pixels in region 1502 are nolonger saturated, and have an average numerical value of about 150numerical counts. Digital image 1601 is stored for later use, along withan indication of its 10 millisecond exposure time.

FIG. 17 shows a similar digital image 1700, collected from region ofinterest 1503 with an exposure time of 10 milliseconds. As is apparent,the pixels are still saturated, so using the techniques described above,region 1503 is further subdivided, shown as regions of interest 1702,1703, and 1704, so that each of the patches of saturated pixels can beimaged separately with an even shorter exposure time.

FIG. 18 shows the results of imaging regions 1702, 1703, and 1704, withshorter exposure times. Regions 1702 and 1703 were successfully imagedwithout saturation at an exposure time of 1 millisecond, but as isshown, region 1704 required an exposure time of 0.5 milliseconds toavoid saturation. These images are usable for HDR imaging and arestored, along with indications of their exposure times.

To incrementally create an initial HDR image, an initially-blank digitalimage 1901 may be first created, having all its pixels set to zerointensity, as shown in FIG. 19. The stored images of regions 1502, 1702,1703, and 1704 are the incrementally placed, starting with the imagehaving the shortest exposure time—in this case the image of region 1704.

Next, the digital images from regions 1702 and 1703 are added, as shownin FIG. 20. Because their exposure time was twice the exposure time ofregion 1704, the numerical values of the pixels corresponding to region1704 in image 1901 are doubled in the process. That is, all of thenumerical values are normalized to the higher exposure time, which is 1millisecond so far.

Finally, digital image 1601 corresponding to region 1502 is placed intoHDR image 1901, as shown in FIG. 21. Because the exposure time ofdigital image 1601 was 10 times the exposure time used to captureregions 1702 and 1703, all of the existing numerical values aremultiplied by 10, to normalize them to the 10 millisecond exposure time.

Once HDR image 1901 has been constructed, accommodating the pixels thatsaturated in initial image 1501, HDR image 1901 can serve as the basisfor further HDR imaging. As additional images are taken in increasinglylong exposure times, the pixels in regions of interest in HDR image 1901can be further normalized to the increasingly long exposure times, andtheir relative brightness preserved throughout the process.

In other embodiments, the stored images, for example the non-saturatedimages of regions 1502, 1702, 1703, and 1704 may be examined to seewhich has the longest exposure time, and each of the images may benormalized and placed into HDR image 1901 in one step by normalizing itsnumerical values directly to the longest exposure time.

The examples above presume that the imaging system is designed so thatthe system electronics have the same usable range as the sensor pixels,and the saturation level of a pixel corresponds to a full-scale readingof the ADC, such as 255 for an 8-bit ADC. However, this is not arequirement, and may only rarely be true. For example, if theelectronics of the system have a wider usable range than the pixelsthemselves, the saturation level of a pixel may be read as less than afull-scale ADC reading, such as 250 for an 8-bit ADC. In that case,identifying saturated pixels in the resulting digital image would meanidentifying pixels having a numerical value of 250 or more (in thisexample), rather than 255.

Similarly, the electronics of the system may have a narrower usablerange than the pixels themselves. For example, an amount of charge lessthan saturation may be converted to a full-scale ADC reading. In thiscase, the ADC saturates while the sensor pixels still have availablecharge capacity. For the purposes of this disclosure, the term“saturated pixel” encompasses this situation, as well as the situationwhere a pixel's charge storage capacity is exceeded. The effect issimilar, in that numerical values read by the system cease to be linearwith light intensity when the ADC range is exceeded.

In some embodiments, pixels may be identified as “saturated” when theyexceed an arbitrary brightness threshold that may be somewhat below thecharge capacity of the pixels and below the full-scale ADC reading. Forexample, in a system with an 8-bit ADC where actual pixel saturation isread as a value of 252, pixels could be identified as saturated whentheir numerical values exceed 245 or a similar threshold. This techniquemay better accommodate noise, temperature variations, and the like.

The embodiments above have been explained in the context of a sensorthat can be globally reset, and that continues to accumulate chargeuntil its next reset, much in the manner of leaving the shutter open ina camera to take a very long exposure. In other embodiments, certainreads may be performed using a “rolling shutter” mode, as is illustratedin FIG. 22. In sensor 2201, rows 2202 a, 2202 b, 2202 c, etc. are resetsequentially starting from first edge 2203 of sensor 2201. A short timelater (the exposure time t), the rows are read out sequentially, alsostarting from first edge 2203. Presuming the exposure time t is shorterthan the time required to read all of the rows, the resets proceedacross the sensor ahead of the reads, separated by a distance thatdepends on the exposure time, but may be a small as one row. In thisway, the exposure time for each individual pixel may be much shorterthan the time required to read the entire sensor. The pixels are not allexposed at the same time, but this has no detrimental effect, as theimage being taken changes very slowly compared with the reading timesinvolved. Portions of sensor 2201, smaller than the entire sensor, maybe read in this way as well.

The above embodiments have been explained primarily in the context of aCMOS image sensor, in which individual pixels, or at least rows ofpixels, can be read directly. In a CMOS sensor, it is typically notnecessary to read the entire sensor if only small region is of interest.

In other embodiments, a CCD sensor may be used. A CCD is similar to aCMOS sensor in that pixels in the sensor accumulate electric charge inproportion to the intensity of light falling on the pixels. However, CCDsensors differ in the way the charge amounts are read.

Rather than reading charges directly from individually-addressablepixels (as in a CMOS sensor), the charges in a CCD are shifted off ofthe sensor in “bucket brigade” style and presented to a charge amplifierthat converts each charge amount to a voltage that can be digitized.

FIG. 23 illustrates a simplified schematic diagram of a CCD sensor 2301.CCD sensor 2301 has a number of pixels 2302 arranged in an array of rowsand columns. To read CCD sensor 2301, the accumulated charges areshifted row-by-row into a shift register 2303, and then pixel-by-pixelthrough shift register 2303 to charge amplifier 2304. Charge amplifier2304 converts each charge to a voltage, which is then converted to anumerical value by an analog-to-digital converter (ADC) 2305 and outputdigitally at 2306. For a CCD sensor, ADC 2305 is typically an externaldevice, and not integrated into the sensor itself.

In CCD sensor 2301, individual pixels 2302 cannot be addressed and readdirectly. In order for the charge of any particular pixel to bemeasured, it must be shifted to charge amplifier 2304. However, it isnot necessary that all charges be converted to numeric values. Forexample, to read the pixels in particular row 2307, the charges in therows below row 2307 may be shifted into shift register 2303 and simplydiscarded immediately, for example flushed to the substrate of CCDsensor 2301, rather than being shifted to charge amplifier 2304. Oncethe charges from row 2307 arrive in shift register 2303, they can beshifted to charge amplifier 2304 and converted. In this way, small areasof sensor 2301 may be read quickly. This technique may be used inembodiments of the invention using CCD sensors, to read small regions ofinterest as quickly as possible.

If the sites in shift register 2303 have a larger charge capacity thanthe pixels 2302, then the readout time can be further reduced bybinning. For example, if the shift register sites 2303 have at leastdouble the charge capacity of the pixels 2302, then the charges from tworows of pixels 2302 can be shifted into shift register 2303 without riskof saturating the shift register sites. The charges in shift register2303 can then be shifted out through charge amplifier 2304 and convertedto numerical values by ADC 2305. In this way, sensor 2301 or a portionof it can be read nearly twice as fast, at the expense of a reduction inimage resolution. If the charge storage sites in shift register 2303have an even larger charge capacity, for example at least three timesthe charge capacity of pixels 2302, then more lines can be binned,resulting in even faster readout, and less risk of saturation of any onepixel 2302.

Sensor 2301 is a full frame CCD sensor, with its sensor area essentiallycompletely filled with light-sensitive pixels. Binning may also be usedin an interline transfer type CCD. In an interline transfer CCD, part ofthe imager area is taken up by charge storage sites that are shieldedfrom light. Charges from the pixels can be shifted into the storagesites a read out at leisure. If the storage sites have a larger chargestorage capacity than the pixels, then binning may be utilized.

In other embodiments, a sensor having multiple taps may be used. In amultiple-tap sensor, there are two or more readout paths that canoperate in parallel, and therefore readout can be accomplished roughlytwice as fast or more than with a single-tap sensor. For example, in aCMOS sensor, two ADCs may be provided, with one half of the pixels beingrouted to one of the ADCs for conversion, and the other half of thepixels being routed to the other ADC for conversion. Any workable numberof taps may be provided.

A similar technique can be used with a CCD sensor. For example, twoshift registers similar to shift register 2303 may be provided onopposite sides of the pixel array. Each of the shift registers isprovided with its own charge amplifier and ADC. Half of the rows may beshifted to each of the two shift registers, enabling reading the sensortwice as fast. Again, any workable number of taps may be used.

Depending on the sensor type and the readout design of the sensor, thesmallest readable region may be a single row of pixels, a single columnof pixels, or even a single pixel.

FIG. 24 illustrates an imaging system 2400 in accordance withembodiments of the invention. Imaging system 2400 comprises anelectronic array light sensor 2401 and a computerized controller 2402.Controller 2402 further comprises a processor 2403 and a memory 2404.Memory 2404 holds instructions that, when executed by processor 2403,cause the system to carry out embodiments of the invention. Memory 2404may hold other kinds of data as well, including image data.

Controller 2402 controls sensor 2401 via one or more control signals2405, and receives data from sensor 2401 via one or more data signals2406.

Sensor 2401 may be a CMOS sensor, a CCD sensor, or another suitable kindof sensor having pixels. Other elements of the system, for example acharge amplifier that may be present with a CCD sensor, are omitted fromFIG. 24.

Any suitable architecture may be used for imaging system 2400. Forexample, control signals 2405 may preferably be digital signals. Datasignals 2406 may be digital signals, for example in the case wheresensor 2401 has its own built-in analog-to-digital converter orconverters. In other embodiments, data signals 2406 may be analogsignals and conversion to digital values may be performed in controller2402. Many other variations are possible.

While embodiments of the invention have been described in the context ofCMOS and CCD sensors, it will be recognized that the claims encompassthe use of other kinds of sensors, including those yet to be developed.

In the claims appended hereto, the term “a” or “an” is intended to mean“one or more.” The term “comprise” and variations thereof such as“comprises” and “comprising,” when preceding the recitation of a step oran element, are intended to mean that the addition of further steps orelements is optional and not excluded. The invention has now beendescribed in detail for the purposes of clarity and understanding.However, those skilled in the art will appreciate that certain changesand modifications may be practiced within the scope of the appendedclaims.

What is claimed is:
 1. A method of image capture, the method comprising:capturing a first digital image of an at least partially luminescenttarget using an electronic array light sensor of a contact imager;identifying one or more saturated pixels in the first digital image;identifying a first region of interest in the first digital image, thefirst region of interest encompassing at least some of the one or moreidentified saturated pixels; and capturing a second digital image of thetarget using the electronic array light sensor of the contact imager,the second digital image encompassing only the first region of interest,and the second digital image being captured with a shorter exposure timethan the first digital image; identifying one or more saturated pixelsin the second digital image; identifying a second region of interestencompassing at least some of the saturated pixels in the second digitalimage, the second region of interest being smaller than the first regionof interest; and capturing a third digital image of the target using theelectronic array light sensor, the third digital image encompassing onlythe second region of interest, and the third digital image beingcaptured with a shorter exposure time than the second digital image. 2.The method of claim 1, wherein the first digital image encompasses theentire electronic array light sensor, and is read as quickly as possiblefrom the electronic array light sensor.
 3. The method of claim 1,wherein the first region of interest encompasses all of the saturatedpixels in the first digital image.
 4. The method of claim 1, wherein thefirst region of interest encompasses a discrete patch of saturatedpixels.
 5. The method of claim 4, wherein the first region of interestencompasses only one of at least two discrete patches of saturatedpixels.
 6. The method of claim 1, further comprising assembling a highdynamic range digital image of the target using at least the first andsecond digital images.
 7. The method of claim 6, further comprising:capturing a long-exposure digital image of the target using theelectronic array light sensor, the long-exposure digital image beingcaptured with an exposure time longer than the exposure time of thefirst digital image; and assembling the high dynamic range digital imageusing at least the first digital image, the second digital image, andthe long-exposure digital image.
 8. The method of claim 1, furthercomprising: assembling a high dynamic range digital image of the targetusing at least the first digital image, the second digital image, andthe third digital image.
 9. The method of claim 1, further comprising:capturing a long-exposure digital image of the target using theelectronic array light sensor, the long-exposure digital image beingcaptured with a longer exposure time than the first digital image; andassembling a high dynamic range digital image of the target using atleast the first digital image and the long-exposure digital image,wherein the second region of interest in the high dynamic range digitalimage includes data derived from the third digital image.
 10. The methodof claim 1, wherein the electronic array light sensor is a complementarymetal oxide semiconductor (CMOS) sensor, and wherein capturing thesecond digital image of the target comprises reading fewer than all ofthe pixels in the electronic array light sensor.
 11. The method of claim1, wherein the electronic array light sensor is a complementary metaloxide semiconductor (CMOS) sensor, and wherein capturing at least one ofthe first digital image and the second digital image comprises the useof a rolling shutter.
 12. The method of claim 1, wherein the electronicarray light sensor is a charge coupled device (CCD) sensor, and whereincapturing the second digital image of the target comprises shifting somecharges from the CCD sensor and discarding them without conversion tonumerical values.
 13. The method of claim 1, wherein the electronicarray light sensor is a charge coupled device (CCD) sensor, and whereincapturing the second digital image of the target comprises binning ofcharges in the CCD sensor.
 14. The method of claim 1, further comprisinglimiting the size of the first region of interest in relation to theelectronic array light sensor.
 15. The method of claim 1, wherein thesecond digital image is captured at a lower resolution than the firstdigital image.
 16. A method of image capture, the method comprising:capturing a first digital image of an at least partially luminescenttarget using an electronic array light sensor of a contact imager;identifying one or more saturated pixels in the first digital image;identifying a first region of interest in the first digital image, thefirst region of interest encompassing at least some of the one or moreidentified saturated pixels; and capturing a second digital image of thetarget using the electronic array light sensor of the contact imager,the second digital image encompassing only the first region of interest,and the second digital image being captured with a shorter exposure timethan the first digital image; identifying one or more saturated pixelsin the second digital image; subdividing the first region of interestinto one or more progressively smaller regions of interest; andcapturing one or more additional digital images of the one or moreprogressively smaller regions of interest using progressively smallerexposure times, until a digital image is obtained having no saturatedpixels.
 17. An imaging device, comprising: a contact imager comprisingan electronic array light sensor having a number of pixels; and acontroller programmed to control operation of the electronic array lightsensor and to receive signals from the electronic array light sensorindicating an intensity of light falling respectively on the pixels ofthe electronic array light sensor, wherein the controller is programmedto: capture a first digital image of an at least partially luminescenttarget using the electronic array light sensor of the contact imager;identify one or more saturated pixels in the first digital image;identify a first region of interest in the first digital image, thefirst region of interest encompassing the one or more identifiedsaturated pixels; and capture a second digital image of the target usingthe electronic array light sensor of the contact imager, the seconddigital image encompassing only the first region of interest, and thesecond digital image being captured with a shorter exposure time thanthe first digital image; identify one or more saturated pixels in thesecond digital image; identify a second region of interest encompassingat least some of the saturated pixels in the second digital image, thesecond region of interest being smaller than the first region ofinterest; and capture a third digital image of the target using theelectronic array light sensor, the third digital image encompassing onlythe second region of interest, and the third digital image beingcaptured with a shorter exposure time than the second digital image. 18.The imaging device of claim 17, wherein the electronic array lightsensor is a complementary metal oxide semiconductor (CMOS) sensor or acharged coupled device (CCD) sensor.
 19. The imaging device of claim 17,wherein the controller is further programmed to construct a high dynamicrange digital image of the target using at least the first digital imageand the second digital image.
 20. The imaging device of claim 17,wherein the electronic array light sensor comprises multiple taps.